Search Tips
- Keyword Search – Use the keyword search field to type your own search terms.
- Resource Type – Use the resource type dropdown to find the type of resource that you want (e.g. article, video, report, file, link, study, etc.).
- Resource Topic – Use the resource topic dropdown to find major themes of the resource that you want (e.g. Women Veterans, Homelessness, Wages). You can select multiple topics from the dropdown.
- Resource Tags – Use the resource tag dropdown to search the resource for keyword or term associated with the resource.
- If you are searching using an acronym, try a second search with the acronym spelled out. For example, if you are searching for resources related to the Davis-Bacon Act, try searching "Davis-Bacon Act" as well as "DBA".
- For more specific results, use quotation marks around phrases.
- For more general results, remove quotation marks to search for each word individually. For example, minimum wage will return all documents that have either the word minimum or the word wage in the description, while “minimum wage” will limit results to those containing that phrase.
Resource Library
In 2023, the Chief Evaluation Office (CEO), in partnership with the Bureau of International Labor Affairs (ILAB), contracted with Westat Insight to explore approaches to measure and increase program provision to underserved and marginalized communities through ILAB’s discretionary grantmaking programs under the Administrative Data Research and Analysis portfolio of studies.
The E2A Tool Kit: Tips for Developing Great Evidence to Action (E2A) Products, produced under the Evidence to Action (E2A) at DOL: Portfolio Project & Process Study, is designed to help research teams plan for and develop effective evidence-to-action research products. While the hope is that the tool kit will be useful for a wider audience, it is written for research contractors who work for the U.S. Department of Labor (DOL) and for DOL staff who review and provide guidance on research contracts.
This guide provides users with a quick overview for launching the Worker Paid Leave Usage Simulation (Worker PLUS) model. The Worker PLUS User Manual provides two options for launching the model (options 1 and 2) and two options for downloading the American Community Survey (ACS) input files to run model simulations (options A and B). This guide focuses on option 1 for quickly launching the model’s graphical user interface (GUI) in Python and option A for downloading the ACS input files. Users following this quick-start guide do not need to have Python installed to launch the GUI.
The infographic explains how the Worker Paid Leave Usage Simulation (Worker PLUS) Model can help researchers and policymakers anticipate the benefits and costs of paid leave policies.
In 2023, the Chief Evaluation Office (CEO) partnered with the Occupational Safety and Health Administration (OSHA) and commissioned Westat to examine the feasibility of using administrative data to conduct an implementation study of the National Construction Safety and Health Achievement Recognition Program (SHARP) Pilot (NCSP) under the Administrative Data Research and Analysis portfolio of studies.
In 2022, the Chief Evaluation Office (CEO) partnered with the Mine Safety and Health Administration (MSHA) and commissioned contractor Summit Consulting, LLC (Summit) to conduct the Black Lung Incidence Study under the Administrative Data Research and Analysis portfolio of studies.
In 2021, the Chief Evaluation Office (CEO) funded contractor Westat Insight and their partner American Institutes for Research to conduct the Explorations in Data Innovations project under the Administrative Data Research and Analysis portfolio of studies. This use case study was designed to explore options around employing machine learning to create and maintain a public-facing, labor-related data catalog.
In the issue brief, researchers use simulation results from the Worker Paid Leave Usage Simulation (Worker PLUS) Model to analyze the impacts of moving from the unpaid leave system under the current Family and Medical Leave Act to a system that includes a paid leave program that adopts the program rules of the existing program in California. The population considered consists of individuals who work in the state of Maryland who meet the eligibility rules of the California program, and among them, the low-wage workers who earn no more than $30,000 annually.
The brief provides a step-by-step guide to performing example simulations using the Worker Paid Leave Usage Simulation (Worker PLUS) model. With this guide, users should be able to replicate the provided example of model running using either the Python or the R simulation engine, and to check how the simulation results compare against actual program data for existing state programs in California, New Jersey, and Rhode Island.
The issue brief provides a benchmarking study of the Worker Paid Leave Usage Simulation (Worker PLUS) Model’s Benefit Financing module. Researchers compare payroll tax revenue estimates from Worker PLUS to actual program administrative data for three state paid leave programs (California, New Jersey, and Rhode Island). The study shows that the Benefit Financing module produces conservative revenue estimates in these cases, by underestimating the payroll tax revenue by about 10% to 15%.